Data is often collected to monitor the operation of industrial machines. Such data collection may be used to diagnose problems, troubleshoot, trend operating changes, or otherwise take data points indicative of machine operation. A variety of data types may be collected, and may include temperature, vibration, and the like. The data collection may be continuous, i.e., using dedicated resources for individual machines or groups of machines. In other cases, data collection may be on-demand, for example, in routine checking and maintenance of the machines. In the latter case, mobile units may be provided that may use sensors that are either permanently or temporarily coupled with the machine being measured.
Such on-demand data collection may, however, be costly in terms of time and resources. For example, if several machines are being checked using a mobile unit, complexity in the operation of the unit may be multiplied and can require significant time allocation. Further, bulkiness of such units may hinder movement between machines, as proceeding between machines being checked. However, a reduction in unit size may reduce functionality, such as the ability to retain measurements from previous operations, which may form the basis for trending operating conditions. Complexity can also introduce the possibility of human error, and thus resources may be expended in training users to operate the units.